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view MS2snoop.R @ 2:a35fde23940e draft
planemo upload commit 7bb8dbe0a0bb34d897daf11c5dd3a92e89c23944
author | workflow4metabolomics |
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date | Wed, 08 Jun 2022 12:37:53 +0000 |
parents | df2672c37732 |
children | c68c94865667 |
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#' #' read and process mspurity W4M files #' create a summary of fragment for each precursor and a graphics of peseudo #' spectra + correlation on which checking of fragment is based on #' V3 try to identify and process multiple files for 1 precursor which may #' occur if different collision energy are used #' V4 elimination of correlation = NA. Correlation is done with precursor, if #' precursor is not present correlation with most intense peak #' author: Jean-Francois Martin #' V5 is versionned, lintR-compliant, packaged, unit-tested, documented and #' tested against data from other labs. #' new maintainer: Lain Pavot - lain.pavot@inrae.fr #' #' @import optparse #' assign("MS2SNOOP_VERSION", "1.0.1") lockBinding("MS2SNOOP_VERSION", globalenv()) assign("MISSING_PARAMETER_ERROR", 1) lockBinding("MISSING_PARAMETER_ERROR", globalenv()) assign("BAD_PARAMETER_VALUE_ERROR", 2) lockBinding("BAD_PARAMETER_VALUE_ERROR", globalenv()) assign("MISSING_INPUT_FILE_ERROR", 3) lockBinding("MISSING_INPUT_FILE_ERROR", globalenv()) assign("NO_ANY_RESULT_ERROR", 255) lockBinding("NO_ANY_RESULT_ERROR", globalenv()) assign("DEFAULT_PRECURSOR_PATH", "peaklist_precursors.tsv") assign("DEFAULT_FRAGMENTS_PATH", "peaklist_fragments.tsv") assign("DEFAULT_COMPOUNDS_PATH", "compounds_pos.txt") assign("DEFAULT_OUTPUT_PATH", "compound_fragments_result.txt") assign("DEFAULT_TOLMZ", 0.01) assign("DEFAULT_TOLRT", 20) assign("DEFAULT_MZDECIMAL", 0) assign("DEFAULT_R_THRESHOLD", 0.85) assign("DEFAULT_MINNUMBERSCAN", 8) assign("DEFAULT_SEUIL_RA", 0.5) lockBinding("DEFAULT_PRECURSOR_PATH", globalenv()) lockBinding("DEFAULT_FRAGMENTS_PATH", globalenv()) lockBinding("DEFAULT_COMPOUNDS_PATH", globalenv()) lockBinding("DEFAULT_OUTPUT_PATH", globalenv()) lockBinding("DEFAULT_TOLMZ", globalenv()) lockBinding("DEFAULT_TOLRT", globalenv()) lockBinding("DEFAULT_MZDECIMAL", globalenv()) lockBinding("DEFAULT_R_THRESHOLD", globalenv()) lockBinding("DEFAULT_MINNUMBERSCAN", globalenv()) lockBinding("DEFAULT_SEUIL_RA", globalenv()) assign("DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD", 0.85) assign("DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA", 0.1) assign("DEFAULT_EXTRACT_FRAGMENTS_TOLMZ", 0.01) assign("DEFAULT_EXTRACT_FRAGMENTS_TOLRT", 60) lockBinding("DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD", globalenv()) lockBinding("DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA", globalenv()) lockBinding("DEFAULT_EXTRACT_FRAGMENTS_TOLMZ", globalenv()) lockBinding("DEFAULT_EXTRACT_FRAGMENTS_TOLRT", globalenv()) ######################################################################## #' @title plot_pseudo_spectra #' @param x #' @param r_threshold #' @param fid #' @param sum_int #' @param vmz #' @param cor_abs_int #' @param refcol #' @param c_name #' @description plot_pseudo_spectra #' function to compute sum of intensities among scans for all #' m/z kept (cor > r_threshold & minimum number of scans) #' and plot pseudo spectra #' x dataframe scan X fragments with scans number in the 1st column and #' ions in next with intensities #' fid file id when several a precursor has been detected in several files plot_pseudo_spectra <- function( x, r_threshold, fid, sum_int, vmz, cor_abs_int, refcol, c_name ) { ## du fait de la difference de nombre de colonne entre la dataframe qui ## inclue les scans en 1ere col, mzRef se decale de 1 refcol <- refcol - 1 ## compute relative intensities max=100% rel_int <- sum_int[-1] rel_int <- rel_int / max(rel_int) ## define max value on vertical axis (need to increase in order to plot the ## label of fragments) ymax <- max(rel_int) + 0.2 * max(rel_int) par(mfrow = c(2, 1)) plot(vmz, rel_int, type = "h", ylim = c(0, ymax), main = c_name) ## low correl coef. will be display in grey cor_low <- which(round(cor_abs_int, 2) < r_threshold) lbmzcor <- sprintf("%s(r=%s)", vmz, round(cor_abs_int, 2)) if (length(cor_low) > 0) { text( vmz[cor_low], rel_int[cor_low], lbmzcor[cor_low], cex = 0.5, col = "grey", srt = 90, adj = 0 ) if (length(vmz) - length(cor_low) > 1) { text( vmz[-c(refcol, cor_low)], rel_int[-c(refcol, cor_low)], lbmzcor[-c(refcol, cor_low)], cex = 0.6, col = 1, srt = 90, adj = 0 ) } } else { if (length(vmz) > 1) { text( vmz[-c(refcol)], rel_int[-c(refcol)], lbmzcor[-c(refcol)], cex = 0.6, col = 1, srt = 90, adj = 0 ) } } text( vmz[refcol], rel_int[refcol], lbmzcor[refcol], cex = 0.8, col = 2, srt = 90, adj = 0 ) ## prepare result file corValid <- (round(cor_abs_int, 2) >= r_threshold) ##nolint object_name_linter cp_res <- data.frame( rep(c_name, length(vmz)), rep(fid, length(vmz)), vmz, cor_abs_int, sum_int[-1], rel_int, corValid ) colnames(cp_res) <- c( "compoundName", "fileid", "fragments_mz", "CorWithPrecursor", "AbsoluteIntensity", "relativeIntensity", "corValid" ) return(cp_res) } #' #' @title extract_fragments #' #' @param precursors the precursor list from mspurity #' @param fragments the fragments list from ms purity #' @param mzref #' @param rtref #' @param c_name #' @param r_threshold default = DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD #' @param seuil_ra default = DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA #' @param tolmz default = DEFAULT_EXTRACT_FRAGMENTS_TOLMZ #' @param tolrt default = DEFAULT_EXTRACT_FRAGMENTS_TOLRT #' @returns #' #' @description #' function for extraction of fragments corresponding to precursors #' detected by MSPurity extract_fragments <- function( ## nolint cyclocomp_linter precursors, fragments, mzref, rtref, c_name, min_number_scan, mzdecimal, r_threshold=DEFAULT_EXTRACT_FRAGMENTS_R_THRESHOLD, seuil_ra=DEFAULT_EXTRACT_FRAGMENTS_SEUIL_RA, tolmz=DEFAULT_EXTRACT_FRAGMENTS_TOLMZ, tolrt=DEFAULT_EXTRACT_FRAGMENTS_TOLRT ) { ## filter precursor in the precursors file based on mz and rt in the ## compound list cat("processing ", c_name, "\n") selected_precursors <- which( (abs(precursors$precurMtchMZ - mzref) <= tolmz) & (abs(precursors$precurMtchRT - rtref) <= tolrt) ) ## check if there is the precursor in the file if (length(selected_precursors) > 0) { sprecini <- precursors[selected_precursors, ] ## check if fragments corresponding to precursor are found in several ## files (collision energy) ## this lead to a processing for each fileid mf <- levels(as.factor(sprecini$fileid)) if (length(mf) > 1 && global_verbose) { cat(" several files detected for this compounds :\n") } for (f in seq_along(mf)) { sprec <- sprecini[sprecini$fileid == mf[f], ] ## selection of fragment in the fragments file with the grpid common in ## both fragments and precursors selfrgt <- levels(as.factor(sprec$grpid)) sfrgt <- fragments[ fragments$grpid %in% selfrgt & fragments$fileid == mf[f], ] ## filter fragments on relative intensity seuil_ra = user defined ## parameter (MSpurity flags could be used here) sfrgtfil <- sfrgt[sfrgt$ra > seuil_ra, ] mznominal <- round(x = sfrgtfil$mz, mzdecimal) sfrgtfil <- data.frame(sfrgtfil, mznominal) ## creation of cross table row=scan col=mz X=ra vmz <- levels(as.factor(sfrgtfil$mznominal)) if (global_verbose) { cat(" fragments :", vmz) } ## mz of precursor in data precursor to check correlation with mz_prec <- paste0("mz", round(mean(sprec$mz), mzdecimal)) for (m in seq_along(vmz)) { ## absolute intensity cln <- c( which(colnames(sfrgtfil) == "acquisitionNum"), which(colnames(sfrgtfil) == "i") ) int_mz <- sfrgtfil[sfrgtfil$mznominal == vmz[m], cln] colnames(int_mz)[2] <- paste0("mz", vmz[m]) ## average intensities of mass in duplicate scans comp_scans <- aggregate(x = int_mz, by = list(int_mz[[1]]), FUN = mean) int_mz <- comp_scans[, -1] if (m == 1) { ds_abs_int <- int_mz } else { ds_abs_int <- merge( x = ds_abs_int, y = int_mz, by.x = 1, by.y = 1, all.x = TRUE, all.y = TRUE ) } } if (global_debug) { print(ds_abs_int) write.table( x = ds_abs_int, file = paste0(c_name, "ds_abs_int.txt"), row.names = FALSE, sep = "\t" ) } ## elimination of mz with less than min_number_scan scans (user defined ## parameter) xmz <- rep(NA, ncol(ds_abs_int) - 1) sum_int <- rep(NA, ncol(ds_abs_int)) nbxmz <- 0 nb_scan_check <- min(nrow(ds_abs_int), min_number_scan) for (j in 2:ncol(ds_abs_int)) { sum_int[j] <- sum(ds_abs_int[j], na.rm = TRUE) if (sum(!is.na(ds_abs_int[[j]])) < nb_scan_check) { nbxmz <- nbxmz + 1 xmz[nbxmz] <- j } } xmz <- xmz[-which(is.na(xmz))] if (length(xmz) > 0) { ds_abs_int <- ds_abs_int[, -c(xmz)] sum_int <- sum_int[-c(xmz)] ## liste des mz keeped decale de 1 avec ds_abs_int vmz <- as.numeric(vmz[-c(xmz - 1)]) } ## reference ion for correlation computing = precursor OR maximum ## intensity ion in precursor is not present refcol <- which(colnames(ds_abs_int) == mz_prec) if (length(refcol) == 0) { refcol <- which(sum_int == max(sum_int, na.rm = TRUE)) } pdf( file = sprintf("%s_processing_file%s.pdf", c_name, mf[f]), width = 8, height = 11 ) par(mfrow = c(3, 2)) ## Pearson correlations between absolute intensities computing cor_abs_int <- rep(NA, length(vmz)) if (length(refcol) > 0) { for (i in 2:length(ds_abs_int)) { cor_abs_int[i - 1] <- cor( x = ds_abs_int[[refcol]], y = ds_abs_int[[i]], use = "pairwise.complete.obs", method = "pearson" ) plot( ds_abs_int[[refcol]], ds_abs_int[[i]], xlab = colnames(ds_abs_int)[refcol], ylab = colnames(ds_abs_int)[i], main = sprintf( "%s corr coeff r=%s", c_name, round(cor_abs_int[i - 1], 2) ) ) } ## plot pseudo spectra res_comp_by_file <- plot_pseudo_spectra( x = ds_abs_int, r_threshold = r_threshold, fid = mf[f], sum_int = sum_int, vmz = vmz, cor_abs_int = cor_abs_int, refcol = refcol, c_name = c_name ) if (f == 1) { res_comp <- res_comp_by_file } } else { res_comp_by_file <- NULL cat(" non detected in fragments file \n") } if (!is.null(res_comp_by_file)) { res_comp <- rbind(res_comp, res_comp_by_file) } if (global_verbose) { cat("\n") } dev.off() } } else { res_comp <- NULL cat(" non detected in precursor file \n") } return(res_comp) } set_global <- function(var, value) { assign(var, value, envir = globalenv()) } set_debug <- function() { set_global("global_debug", TRUE) } unset_debug <- function() { set_global("global_debug", FALSE) } set_verbose <- function() { set_global("global_verbose", TRUE) } unset_verbose <- function() { set_global("global_verbose", FALSE) } create_parser <- function() { parser <- optparse::OptionParser() parser <- optparse::add_option( parser, c("-v", "--verbose"), action = "store_true", default = FALSE, help = paste( "[default %default]", "Print extra output" ) ) parser <- optparse::add_option( parser, c("-V", "--version"), action = "store_true", default = FALSE, help = "Prints version and exits" ) parser <- optparse::add_option( parser, c("-d", "--debug"), action = "store_true", default = FALSE, help = paste( "[default %default]", "Print debug outputs" ) ) parser <- optparse::add_option( parser, c("-o", "--output"), type = "character", default = DEFAULT_OUTPUT_PATH, action = "store", help = "Path to the output file [default %default]" ) parser <- optparse::add_option( parser, c("-p", "--precursors"), type = "character", default = DEFAULT_PRECURSOR_PATH, action = "store", help = "Path to the precursors file [default %default]" ) parser <- optparse::add_option( parser, c("-f", "--fragments"), type = "character", default = DEFAULT_FRAGMENTS_PATH, action = "store", help = "Path to the fragments file [default %default]" ) parser <- optparse::add_option( parser, c("-c", "--compounds"), type = "character", default = DEFAULT_COMPOUNDS_PATH, action = "store", help = "Path to the compounds file [default %default]" ) parser <- optparse::add_option( parser, c("--tolmz"), type = "numeric", action = "store", default = DEFAULT_TOLMZ, metavar = "number", help = paste( "[default %default]", "Tolerance for MZ (in Dalton) to match the standard in the compounds" ) ) parser <- optparse::add_option( parser, c("--tolrt"), type = "integer", action = "store", default = DEFAULT_TOLRT, metavar = "number", help = paste( "[default %default]", "RT (in seconds) to match the standard in the compounds" ) ) parser <- optparse::add_option( parser, c("--seuil_ra"), type = "numeric", action = "store", default = DEFAULT_SEUIL_RA, metavar = "number", help = paste( "[default %default]", "relative intensity threshold" ), ) parser <- optparse::add_option( parser, c("--mzdecimal"), type = "integer", default = DEFAULT_MZDECIMAL, action = "store", help = paste( "[default %default]", "Number of decimal to write for MZ" ), metavar = "number" ) parser <- optparse::add_option( parser, c("--r_threshold"), type = "integer", default = DEFAULT_R_THRESHOLD, action = "store", help = paste( "[default %default]", "R-Pearson correlation threshold between precursor and fragment", "absolute intensity" ), metavar = "number" ) parser <- optparse::add_option( parser, c("--min_number_scan"), type = "numeric", action = "store", default = DEFAULT_MINNUMBERSCAN, help = paste( "[default %default]", "Fragments are kept if there are found in a minimum number", "of min_number_scan scans" ), metavar = "number" ) return(parser) } stop_with_status <- function(msg, status) { message(sprintf("Error: %s", msg)) message(sprintf("Error code: %s", status)) base::quit(status = status) } check_args_validity <- function(args) { ## nolint cyclocomp_linter sysvars <- Sys.getenv() sysvarnames <- names(sysvars) if (length(args$output) == 0 || nchar(args$output[1]) == 0) { stop_with_status( "Missing output parameters. Please set it with --output.", MISSING_PARAMETER_ERROR ) } if (length(args$precursors) == 0 || nchar(args$precursors[1]) == 0) { stop_with_status( "Missing precursors parameters. Please set it with --precursors.", MISSING_PARAMETER_ERROR ) } if (length(args$fragments) == 0 || nchar(args$fragments[1]) == 0) { stop_with_status( "Missing fragments parameters. Please set it with --fragments.", MISSING_PARAMETER_ERROR ) } if (length(args$compounds) == 0 || nchar(args$compounds[1]) == 0) { stop_with_status( "Missing compounds parameters. Please set it with --compounds.", MISSING_PARAMETER_ERROR ) } if (!file.exists(args$precursors)) { stop_with_status( sprintf( "Precursors file %s does not exist or cannot be accessed.", args$precursors ), MISSING_INPUT_FILE_ERROR ) } if (!file.exists(args$fragments)) { stop_with_status( sprintf( "Fragments file %s does not exist or cannot be accessed.", args$fragments ), MISSING_INPUT_FILE_ERROR ) } if (!file.exists(args$compounds)) { stop_with_status( sprintf( "Compounds file %s does not exist or cannot be accessed.", args$compounds ), MISSING_INPUT_FILE_ERROR ) } if ( "_GALAXY_JOB_HOME_DIR" %in% sysvarnames || "_GALAXY_JOB_TMP_DIR" %in% sysvarnames || "GALAXY_MEMORY_MB" %in% sysvarnames || "GALAXY_MEMORY_MB_PER_SLOT" %in% sysvarnames || "GALAXY_SLOTS" %in% sysvarnames ) { check_galaxy_args_validity(args) } } check_galaxy_args_validity <- function(args) { if (!file.exists(args$output)) { stop_with_status( sprintf( "Output file %s does not exist or cannot be accessed.", args$output ), MISSING_INPUT_FILE_ERROR ) } } main <- function(args) { if (args$version) { cat(sprintf("%s\n", MS2SNOOP_VERSION)) base::quit(status = 0) } sessionInfo() check_args_validity(args) if (args$debug) { set_debug() } if (args$verbose) { set_verbose() } ## MSpurity precursors file precursors <- read.table( file = args$precursors, header = TRUE, sep = "\t", quote = "\"" ) ## MSpurity fragments file fragments <- read.table( file = args$fragments, header = TRUE, sep = "\t", quote = "\"" ) ## list of compounds : col1=Name of molecule, col2=m/z, col3=retention time compounds <- read.table( file = args$compounds, sep = "\t", quote = "\"", header = TRUE ) res_all <- NULL for (i in seq_len(nrow(compounds))) { ## loop execution for all compounds in the compounds file res_cor <- NULL res_cor <- extract_fragments( precursors = precursors, fragments = fragments, mzref = compounds[[2]][i], rtref = compounds[[3]][i], c_name = compounds[[1]][i], min_number_scan = args$min_number_scan, mzdecimal = args$mzdecimal, r_threshold = args$r_threshold, seuil_ra = args$seuil_ra, tolmz = args$tolmz, tolrt = args$tolrt ) if (!is.null(res_cor)) { if (is.null(res_all)) { res_all <- res_cor } else { res_all <- rbind(res_all, res_cor) } } } if (is.null(res_all)) { stop_with_status("No result at all!", NO_ANY_RESULT_ERROR) } write.table( x = res_all, file = args$output, sep = "\t", row.names = FALSE ) } unset_debug() unset_verbose() args <- optparse::parse_args(create_parser()) main(args) warnings()